A knowledge-based multi-dimension discrete common cause failure model

Abstract

Common cause failure (CCF) is analyzed as a manifestation of the probabilistic characteristics of component failure rate/probability stemming from stochastic environment load. CCF revolved concepts, such as ‘root cause’ and ‘coupling mechanism’ are interpreted mathematically from the viewpoint of random environment load bringing about failure dependency. Opinions about ‘inherent CCF’ and ‘additional CCF’, ‘absolute CCF’ and ‘relative CCF’ are presented and discussed. An easy-to-use CCF model is developed through multi-dimension environment load-component strength interference analysis and knowledge based parameter discretization. Owing to its strict statistical foundation, such a model has the ability of estimating component failure rate/probability and common cause failure rates/probabilities consistently, dealing with low redundancy system CCF and high redundancy system CCF uniformly, and predicting high multiplicity failure rate/probability based on low multiplicity failure data satisfactorily.